{"id":"https://openalex.org/W2505626792","doi":"https://doi.org/10.1145/2851613.2851891","title":"A new time series classification approach based on recurrence quantification analysis and Gabor filter","display_name":"A new time series classification approach based on recurrence quantification analysis and Gabor filter","publication_year":2016,"publication_date":"2016-04-04","ids":{"openalex":"https://openalex.org/W2505626792","doi":"https://doi.org/10.1145/2851613.2851891","mag":"2505626792"},"language":"en","primary_location":{"id":"doi:10.1145/2851613.2851891","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851613.2851891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068027966","display_name":"Angelo M. e Silva","orcid":"https://orcid.org/0000-0003-2660-4817"},"institutions":[{"id":"https://openalex.org/I122558511","display_name":"Universidade Federal de Mato Grosso do Sul","ror":"https://ror.org/0366d2847","country_code":"BR","type":"education","lineage":["https://openalex.org/I122558511"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Angelo Silva","raw_affiliation_strings":["UFMS - FACOM, Campo Grande, MS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UFMS - FACOM, Campo Grande, MS, Brazil","institution_ids":["https://openalex.org/I122558511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047727871","display_name":"Renato Porf\u00edrio Ishii","orcid":"https://orcid.org/0000-0003-0825-8420"},"institutions":[{"id":"https://openalex.org/I122558511","display_name":"Universidade Federal de Mato Grosso do Sul","ror":"https://ror.org/0366d2847","country_code":"BR","type":"education","lineage":["https://openalex.org/I122558511"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Renato Ishii","raw_affiliation_strings":["UFMS - FACOM, Campo Grande, MS, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UFMS - FACOM, Campo Grande, MS, Brazil","institution_ids":["https://openalex.org/I122558511"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2553,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53034301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"955","last_page":"957"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recurrence-quantification-analysis","display_name":"Recurrence quantification analysis","score":0.7833231091499329},{"id":"https://openalex.org/keywords/recurrence-plot","display_name":"Recurrence plot","score":0.7206361293792725},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6973620057106018},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6875947713851929},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6595678925514221},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6532694697380066},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5047875642776489},{"id":"https://openalex.org/keywords/gabor-filter","display_name":"Gabor filter","score":0.4959283769130707},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4730372130870819},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4696749150753021},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.4448786973953247},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4364653527736664},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.430266797542572},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3457021415233612},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2649329602718353},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1624840795993805},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.1333337128162384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11719653010368347}],"concepts":[{"id":"https://openalex.org/C43456602","wikidata":"https://www.wikidata.org/wiki/Q7303254","display_name":"Recurrence quantification analysis","level":3,"score":0.7833231091499329},{"id":"https://openalex.org/C173134143","wikidata":"https://www.wikidata.org/wiki/Q2797953","display_name":"Recurrence plot","level":3,"score":0.7206361293792725},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6973620057106018},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6875947713851929},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6595678925514221},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6532694697380066},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5047875642776489},{"id":"https://openalex.org/C2779883129","wikidata":"https://www.wikidata.org/wiki/Q2447890","display_name":"Gabor filter","level":3,"score":0.4959283769130707},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4730372130870819},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4696749150753021},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.4448786973953247},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4364653527736664},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.430266797542572},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3457021415233612},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2649329602718353},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1624840795993805},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.1333337128162384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11719653010368347},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2851613.2851891","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851613.2851891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320323354","display_name":"Funda\u00e7\u00e3o de Apoio ao Desenvolvimento do Ensino, Ci\u00eancia e Tecnologia do Estado de Mato Grosso do Sul","ror":"https://ror.org/05jtrt935"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2010214994","https://openalex.org/W2010351815","https://openalex.org/W2044465660","https://openalex.org/W2053154970","https://openalex.org/W2081681829","https://openalex.org/W2083361829","https://openalex.org/W2096451472","https://openalex.org/W2125148312","https://openalex.org/W2156372254","https://openalex.org/W6663855623"],"related_works":["https://openalex.org/W4236831073","https://openalex.org/W4385146532","https://openalex.org/W2128285247","https://openalex.org/W4309197050","https://openalex.org/W4310481254","https://openalex.org/W2950325250","https://openalex.org/W1870609992","https://openalex.org/W4297688580","https://openalex.org/W2889018780","https://openalex.org/W2952356350"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,41],"new":[4],"data":[5,34,83],"stream":[6,84,102],"preprocessing":[7,92],"approach":[8,98],"based":[9],"on":[10,82],"texture":[11,61],"analysis":[12,71],"from":[13,58],"Recurrence":[14],"Plot":[15],"(RP).":[16],"We":[17,32],"adopt":[18],"12":[19],"real":[20],"datasets":[21],"related":[22],"to":[23,64,94],"sound":[24],"recognition,":[25],"signals":[26],"processing,":[27],"chemistry":[28],"reactions":[29],"and":[30,52,68,115],"others.":[31],"consider":[33],"streams":[35],"as":[36,107,125],"discrete":[37],"time":[38],"series":[39],"with":[40,55],"fixed":[42],"number":[43],"of":[44,76,112],"observations.":[45],"Classifier":[46],"models":[47],"were":[48],"created":[49],"using":[50,60],"SVM":[51],"C5.0":[53],"algorithms":[54],"features":[56,108],"extracted":[57],"RP":[59],"descriptors":[62],"like":[63],"Gabor":[65],"filter,":[66],"GLCM":[67],"DCT-2D.":[69],"Our":[70],"shows":[72],"that":[73,103,122],"the":[74,91,119],"influence":[75],"stochastic-deterministic":[77],"rate":[78],"obtained":[79],"by":[80],"RQA":[81],"reconstructed":[85],"in":[86,109,116],"phase":[87],"space":[88],"have":[89],"motivated":[90],"step":[93],"classification,":[95],"outperforming":[96],"another":[97],"applied":[99],"an":[100],"audio":[101],"uses":[104,123],"model's":[105],"coefficients":[106],"around":[110,117],"16%":[111],"average":[113],"accuracy":[114],"67.66%":[118],"state-of-art":[120],"algorithm":[121],"distance":[124],"measure.":[126]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}